The ability to process uniformly across a monolithic substrate and/or across a series of monolithic substrates is advantageous for manufacturing efficiency and cost effectiveness, as well as repeatability and control. However, uniform processing across an entire substrate can be disadvantageous when optimizing, qualifying or investigating new materials, new processes, and/or new process sequence integration schemes, since the entire substrate is nominally made the same using the same materials, processes and process sequence integration scheme. Each so processed substrate represents in essence only one possible variation per substrate. Thus, the full wafer uniform processing under conventional processing techniques results in fewer data points per substrate, longer times to accumulate a wide variety of data and higher costs associated with obtaining such data.
Combinatorial processing enables a more efficient evaluation of techniques that may eventually become integrated into a conventional processing scheme. When performing combinatorial processing it is desirable to perform as many tests in as short a time frame as is feasible. However, current combinatorial chambers come up against limitations in the amount of data that can be gathered from a single substrate, especially with respect to plasma processing chambers. Accordingly, there is a need to be able to more efficiently screen and analyze an array of materials, processes, and process sequence integration schemes across a substrate in order to more efficiently evaluate alternative materials, processes, and process sequence integration schemes for semiconductor manufacturing processes.